Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns.

The ongoing shift towards a more decentralized and renewable energy system in Germany requires extensive modifications to existing grids and their operating principlesespecially at the distribution level. Furthermore, the integration of e-mobility will have a significant effect on distribution grids. Smart distribution systems are one way of handling these new supply scenarios. Hence, a self-sustaining monitoring and control system for LV-grids has been developed. It monitors the power flow situation and is able to control the grid if necessary. The system has been implemented in four LV-grids in Germany. The present paper describes the automation system and our initial experience with this smart grid approach.

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